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Qualcomm Multiple roles in Machine Learning & Deep Learning CVPR 2023 - Interns and Full Times in Washington - Remote, Washington

Company:

Qualcomm Technologies, Inc.

Job Area:

Engineering Group, Engineering Group > Machine Learning Researcher

General Summary:

Qualcomm AI Research is looking for world-class researchers in deep learning to join a high-caliber team of engineers inventing machine-learning technology to provide best-in-class solutions while running with the most efficient use of power, memory, and computation. To learn more check here -

  • Artificial Intelligence Research | Qualcomm (https://www.qualcomm.com/research/artificial-intelligence/ai-research)

Members of our team are part of a multi-disciplinary core research group within Qualcomm which spans software, hardware, and systems. Our members contribute technology deployed worldwide by partnering with our business teams across mobile, compute, automotive, cloud, and IOT. We also perform and publish state-of-the-art research on a wide range of topics in machine-learning, ranging from general theory to techniques that enable deployment on resource-constrained devices. Our research team has demonstrated first-in-the-world research and proof-of-concepts in areas such model efficiency, neural video codecs, video semantic segmentation, federated learning, and wireless RF sensing (https://www.qualcomm.com/ai-research), has won major research competitions such as the visual wake word challenge, and converted leading research into best-in-class user-friendly tools such as Qualcomm Innovation Center’s AI Model Efficiency Toolkit ( https://github.com/quic/aimet ). We recently demonstrated (https://www.qualcomm.com/news/onq/2023/02/worlds-first-on-device-demonstration-of-stable-diffusion-on-android) the feasibility of running a foundation model (stable diffusion) with >1 billion parameters on an Android phone within tens of seconds after performing our full-stack AI optimizations on the model.

Role responsibility can include both, applied and fundamental research in the field of machine learning with development focus in one or many of the following areas:

  • Conducts fundamental machine learning research to create new models or new training methods in various technology areas, e.g. large language models, deep generative models (VAE, Normalizing-Flow, ARM, etc), Bayesian deep learning, equivariant CNNs, adversarial learning, diffusion models, active learning, Bayesian optimizations, unsupervised learning, and ML combinatorial optimization using tools like graph neural networks, learned message-passing heuristics, and reinforcement learning.

  • Drives systems innovations for model efficiency advancement on device as well as in the cloud. This includes auto-ML methods (model-based, sampling based, back-propagation based) for model compression, quantization, architecture search, and kernel/graph compiler/scheduling with or without systems-hardware co-design.

  • Performs advanced platform research to enable new machine learning compute paradigms, e.g., compute in memory, on-device learning/training, edge-cloud distributed/federated learning, causal and language-based reasoning.

  • Creates new machine learning models for advanced use cases that achieve state-of-the-art performance and beyond. The use cases can broadly include computer vision, audio, speech, NLP, image, video, power management, wireless, graphics, and chip design

  • Design, develop & test software for machine learning frameworks that optimize models to run efficiently on edge devices. Candidate is expected to have strong interest and deep passion on making leading-edge deep learning algorithms work on mobile/embedded platforms for the benefit of end users.

  • Research, design, develop, enhance, and implement different components of machine learning compiler for HW Accelerators.

  • Design, implement and train DL/RL algorithms in high-level languages/frameworks (PyTorch and TensorFlow).

Minimum Qualifications:

• Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

OR

PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field.

• 6+ months of experience developing and/or optimizing machine learning models, systems, platforms, or methods.

Click here to access resources related to internship opportunities:

  • US-based internship opportunities (https://qualcommuniversityhiring.splashthat.com/)

  • Netherlands-based internship opportunities

Here are some of the Research / Engineering opportunities we are actively hiring in different regions - Your application will be reviewed by multiple hiring teams that are hiring for these positions.

  • Machine Learning Compilers Engineer – Markham

  • Deep Learning Researcher - (Qualcomm Research, Amsterdam)

  • Deep Learning Researcher – San Diego

  • Machine Learning Framework Engineer: Distributed / On-Device Training (Sr. Engineer) – San Diego

  • System-2 Deep Learning and Neural Reasoning Researcher – Markham

  • Deep Learning Systems/Hardware Engineer – San Diego

  • Machine Learning Compilers & Optimizations – San Diego

  • Embedded/System Software Engineer – San Diego

  • AI Model Optimization Tools Developer – San Diego

  • Machine Learning Researcher – San Diego

  • Machine Learning Research Engineer – On-device learning – Seoul

  • Machine Learning Evaluation Engineer– Qualcomm Research – Seoul, San Diego

  • Deep Learning SW Engineer– Qualcomm Research – Seoul

  • AIMET Systems Engineer – San Diego

  • On-device Learning – San Diego

  • Optimization Engineer – San Diego

  • ML/AI Cloud Engineer – San Diego

  • Compiler Developer – New York, Remote , Washington - Remote

  • Full Stack C++ Developer for ML Frameworks on Mobile – Markham, San Diego

  • AI Research Engineer – Communications (remote friendly)

Although this role has some expected minor physical activity, this should not deter otherwise qualified applicants from applying. If you are an individual with a physical or mental disability and need an accommodation during the application/hiring process, please call Qualcomm’s toll-free number found here (https://qualcomm.service-now.com/hrpublic?id=hr_public_article_view&sysparm_article=KB0039028) for assistance. Qualcomm will provide reasonable accommodations, upon request, to support individuals with disabilities as part of our ongoing efforts to create an accessible workplace.

Qualcomm is an equal opportunity employer and supports workforce diversity.

To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.

EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.

Pay range:

$150,500.00 - $225,500.00

The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer!

If you would like more information about this role, please contact Qualcomm Careers (http://www.qualcomm.com/contact/corporate) .

EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.

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